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⚡ Source: ReedRef: 56900109

Python Back-end Developer

Initialize·Camden, London·Posted 1 week ago
💰 £40-60k/year
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Job description

Original text imported from Reed

Backend Python Developer (AI) - Remote - UK - excellent opportunity to join this innovative and fast-growing AI tech. organisation!

Skills/experience

  • 2+ years solid commercial Python coding experience (backend, API development would be great).
  • Good understanding of Docker, and scalable distributed systems.
  • An Agile mindset and Experience working in agile teams, using Github for CI/CD, branching, pull requests, and automated testing.

Nice to have:

  • Kubernetes
  • Comfortable with VS Code, ideally with AI coding tools like Copilot or VS Code agents.
  • Understanding/experience of cloud-native patterns, and scalable architecture.
  • Experience with Azure’s native AI stack (AI Foundry, AI Search, Cosmos DB, AKS).
  • Interest in experimenting with new AI frameworks and tools.

Role

  • Code back end solutions confidently in Python, design and implement scalable architecture using cloud-native tools.
  • Build and deploy AI-first features using Azure AI Foundry, Docker and AKS.
  • Use Visual Studio Code (ideally with GitHub Copilot or similar AI coding assistants)
  • Collaborate in a tight feedback loop: branch, commit, pull, test, ship — all through Github.
  • Write unit tests and ship quality code, not just quick fixes.
  • Participate in sprints and daily stand-ups

Why join

  • An excellent opportunity to join an incredible team, organisation - work lean, iterate fast, and learn quickly - perfect role for a Python Back-end Developer with an Agile mindset who is curious, flexible, collaborative, unafraid to try new things and help design and build their AI platform.


SpeedCV AI

Key skills

AI-extracted from the job advert

Must-have skills
Python backend developmentAPI developmentDockerDistributed systemsAgile methodologyGitHub CI/CDUnit testing
Nice-to-have
KubernetesVS CodeGitHub CopilotAzure AI FoundryAzure AI SearchAzure Cosmos DBAzure Kubernetes ServiceCloud-native architecture
Soft skills
CollaborationCuriosityFlexibilityAdaptabilityCommunicationProblem solving
SpeedCV AI

Application advice

5 AI-generated recommendations to maximise your chances.

1

⭐ Highlight your Python backend and API development experience prominently as this is the core requirement mentioned throughout the advert

2

🐳 Emphasise Docker containerisation skills and any Kubernetes experience since these are key infrastructure requirements

3

☁️ Showcase Azure cloud experience, particularly AI Foundry, AI Search, or Cosmos DB if you have them as nice-to-haves

4

🤖 Mention any experience with AI coding tools like GitHub Copilot or VS Code extensions to align with their tech-forward approach

5

📊 Quantify your Agile experience: 'Delivered 15 features across 8 sprints using GitHub CI/CD pipelines'

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Suggested CV bullets

3 bullets our AI drafted for this specific advert, mirroring its ATS keywords.

How to tailor your CV

Add these 3 bullets under your most recent experience:

  • Developed 12 Python APIs using Docker containers, achieving 99.8% uptime across distributed microservices architecture
  • Implemented GitHub CI/CD pipelines reducing deployment time from 45 to 8 minutes while maintaining 100% test coverage
  • Built scalable backend services handling 50,000+ daily requests using Azure cloud-native patterns and Kubernetes orchestration

Free to copy — tailoring requires a 30-sec CV upload.

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AI cover letter

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We've drafted a cover letter for Initialize. Preview the opening, then unlock the full personalised version.

Letter preview — tailored to Initialize

Dear Hiring Manager,

Initialize's AI-first approach to backend development is exactly the direction I want my career to take, which is why I'm excited to apply for the Python Backend Developer role. My 3 years of commercial Python experience combined with Docker containerisation and API development skills align perfectly with your technical requirements.

My background in building scalable distributed systems using cloud-native patterns would enable me to contribute immediately to your Azure AI platform development. I've consistently delivered quality code through GitHub CI/CD pipelines while maintaining the tight feedback loops essential for agile development.

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SpeedCV AI

Interview questions

10 questions generated from this advert.

Technical

  • How would you design a scalable Python API architecture using Docker and Kubernetes?
  • Explain your approach to implementing CI/CD pipelines with GitHub for Python applications
  • How do you handle distributed system challenges when building backend services?
  • What's your experience with Azure AI services like AI Foundry or Cosmos DB?
  • How do you structure unit tests for Python backend applications?

Behavioural

  • Tell me about a time you had to learn a new AI framework or tool quickly
  • Describe a situation where you collaborated closely with a team using Agile methodology
  • Give an example of when you had to iterate fast on a feature based on feedback
  • How do you handle working in a fast-paced, experimental environment?
  • Tell me about a time you had to balance code quality with delivery speed
SpeedCV AINEW

STAR answer examples

Model answers using the Situation-Task-Action-Result framework. Adapt to your own experience.

1Question

Tell me about a time you had to learn a new AI framework or tool quickly

When our team needed to integrate machine learning capabilities into our Python backend, I had 2 weeks to learn TensorFlow Serving. I started by building a simple image classification API using Docker containers, then gradually added complexity. I created a proof-of-concept that processed 1,200 requests per hour with 94% accuracy. The key was breaking down the learning into daily milestones and getting feedback from senior developers. This approach helped me deliver the ML integration on schedule and it became the foundation for 3 additional AI features.
2Question

Describe a situation where you collaborated closely with a team using Agile methodology

During a critical API redesign project, our 5-person team used 2-week sprints with daily stand-ups. I was responsible for the authentication service that 4 other microservices depended on. I broke my work into small, testable chunks and used GitHub pull requests for continuous feedback. When integration issues emerged in week 3, our daily communication helped us pivot quickly. I pair-programmed with 2 teammates to resolve the blockers within 48 hours. The collaborative approach meant we delivered the new API 3 days ahead of schedule with zero post-deployment issues.

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